| Best model | name | model_type | metric_type | metric_value | train_time | single_prediction_time |
|---|---|---|---|---|---|---|
| 1_Linear | Linear | average_precision | 0.981151 | 37.12 | 0.0285 | |
| 2_Default_LightGBM | LightGBM | average_precision | 0.984335 | 33.85 | 0.0133 | |
| 3_Default_Xgboost | Xgboost | average_precision | 0.979549 | 33.35 | 0.0228 | |
| 4_Default_CatBoost | CatBoost | average_precision | 0.987349 | 34.17 | 0.0333 | |
| 5_Default_NeuralNetwork | Neural Network | average_precision | 0.971355 | 32.2 | 0.0405 | |
| 6_Default_RandomForest | Random Forest | average_precision | 0.978456 | 35.77 | 0.1487 | |
| 11_LightGBM | LightGBM | average_precision | 0.984562 | 34.78 | 0.0148 | |
| 7_Xgboost | Xgboost | average_precision | 0.981538 | 35.11 | 0.0137 | |
| 15_CatBoost | CatBoost | average_precision | 0.988065 | 35.58 | 0.0174 | |
| 19_RandomForest | Random Forest | average_precision | 0.987365 | 38.27 | 0.1872 | |
| 23_NeuralNetwork | Neural Network | average_precision | 0.978522 | 32.79 | 0.0313 | |
| 12_LightGBM | LightGBM | average_precision | 0.981605 | 34.55 | 0.0182 | |
| 8_Xgboost | Xgboost | average_precision | 0.979431 | 33.48 | 0.0192 | |
| 16_CatBoost | CatBoost | average_precision | 0.981597 | 36.16 | 0.0246 | |
| 20_RandomForest | Random Forest | average_precision | 0.984126 | 37.24 | 0.1341 | |
| 24_NeuralNetwork | Neural Network | average_precision | 0.976907 | 34.78 | 0.037 | |
| 13_LightGBM | LightGBM | average_precision | 0.985243 | 35.9 | 0.0128 | |
| 9_Xgboost | Xgboost | average_precision | 0.911635 | 34.94 | 0.0144 | |
| 17_CatBoost | CatBoost | average_precision | 0.980034 | 36.34 | 0.0179 | |
| 21_RandomForest | Random Forest | average_precision | 0.968446 | 39.55 | 0.1381 | |
| 25_NeuralNetwork | Neural Network | average_precision | 0.969369 | 34.73 | 0.0367 | |
| 14_LightGBM | LightGBM | average_precision | 0.982671 | 36.43 | 0.0127 | |
| 10_Xgboost | Xgboost | average_precision | 0.500365 | 33.86 | 0.0145 | |
| 18_CatBoost | CatBoost | average_precision | 0.985217 | 36.49 | 0.0169 | |
| 22_RandomForest | Random Forest | average_precision | 0.973307 | 38.21 | 0.1672 | |
| 26_NeuralNetwork | Neural Network | average_precision | 0.97895 | 34.08 | 0.0343 | |
| 15_CatBoost_GoldenFeatures | CatBoost | average_precision | 0.987348 | 39.45 | 0.0404 | |
| 19_RandomForest_GoldenFeatures | Random Forest | average_precision | 0.981939 | 40.23 | 0.1546 | |
| 4_Default_CatBoost_GoldenFeatures | CatBoost | average_precision | 0.989526 | 37.73 | 0.0374 | |
| 27_CatBoost_GoldenFeatures | CatBoost | average_precision | 0.99044 | 37.09 | 0.0348 | |
| 28_CatBoost | CatBoost | average_precision | 0.97874 | 37.51 | 0.013 | |
| 29_CatBoost | CatBoost | average_precision | 0.990262 | 38.18 | 0.0183 | |
| 30_RandomForest | Random Forest | average_precision | 0.986077 | 40.24 | 0.1715 | |
| 31_RandomForest | Random Forest | average_precision | 0.985326 | 40.35 | 0.1417 | |
| 32_LightGBM | LightGBM | average_precision | 0.985875 | 37.62 | 0.0113 | |
| 33_LightGBM | LightGBM | average_precision | 0.984718 | 37.79 | 0.0159 | |
| 34_LightGBM | LightGBM | average_precision | 0.9859 | 37.05 | 0.0113 | |
| 35_CatBoost_GoldenFeatures | CatBoost | average_precision | 0.989239 | 38.26 | 0.0364 | |
| 36_CatBoost_GoldenFeatures | CatBoost | average_precision | 0.986614 | 39.03 | 0.0388 | |
| 37_CatBoost | CatBoost | average_precision | 0.985173 | 38.25 | 0.0144 | |
| 38_CatBoost | CatBoost | average_precision | 0.981361 | 39.14 | 0.0157 | |
| the best | Ensemble | Ensemble | average_precision | 0.992985 | 2.69 | 0.1873 |
average_precision
33.0 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.693206 | nan |
| auc | 0.500868 | nan |
| f1 | 0.666667 | 0.452935 |
| accuracy | 0.502183 | 0.505075 |
| precision | 0.501818 | 0.505075 |
| recall | 1 | 0.452935 |
| mcc | 0.00445767 | 0.505075 |
| score | threshold | |
|---|---|---|
| logloss | 0.693206 | nan |
| auc | 0.500868 | nan |
| f1 | 0.547619 | 0.505075 |
| accuracy | 0.502183 | 0.505075 |
| precision | 0.501818 | 0.505075 |
| recall | 0.60262 | 0.505075 |
| mcc | 0.00445767 | 0.505075 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 92 | 137 |
| Labeled as 1 | 91 | 138 |
average_precision
34.0 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.195958 | nan |
| auc | 0.980778 | nan |
| f1 | 0.955947 | 0.533395 |
| accuracy | 0.956332 | 0.533395 |
| precision | 1 | 0.928398 |
| recall | 1 | 0.00380183 |
| mcc | 0.912803 | 0.533395 |
| score | threshold | |
|---|---|---|
| logloss | 0.195958 | nan |
| auc | 0.980778 | nan |
| f1 | 0.955947 | 0.533395 |
| accuracy | 0.956332 | 0.533395 |
| precision | 0.964444 | 0.533395 |
| recall | 0.947598 | 0.533395 |
| mcc | 0.912803 | 0.533395 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 221 | 8 |
| Labeled as 1 | 12 | 217 |
average_precision
33.7 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.156221 | nan |
| auc | 0.97992 | nan |
| f1 | 0.960699 | 0.451329 |
| accuracy | 0.960699 | 0.451329 |
| precision | 1 | 0.99819 |
| recall | 1 | 1.13086e-05 |
| mcc | 0.922665 | 0.718673 |
| score | threshold | |
|---|---|---|
| logloss | 0.156221 | nan |
| auc | 0.97992 | nan |
| f1 | 0.960699 | 0.451329 |
| accuracy | 0.960699 | 0.451329 |
| precision | 0.960699 | 0.451329 |
| recall | 0.960699 | 0.451329 |
| mcc | 0.921397 | 0.451329 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 220 | 9 |
| Labeled as 1 | 9 | 220 |
average_precision
35.2 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.18233 | nan |
| auc | 0.982418 | nan |
| f1 | 0.958785 | 0.452312 |
| accuracy | 0.958515 | 0.452312 |
| precision | 1 | 0.928244 |
| recall | 1 | 2.76086e-05 |
| mcc | 0.917109 | 0.452312 |
| score | threshold | |
|---|---|---|
| logloss | 0.18233 | nan |
| auc | 0.982418 | nan |
| f1 | 0.958785 | 0.452312 |
| accuracy | 0.958515 | 0.452312 |
| precision | 0.952586 | 0.452312 |
| recall | 0.965066 | 0.452312 |
| mcc | 0.917109 | 0.452312 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 218 | 11 |
| Labeled as 1 | 8 | 221 |
average_precision
35.6 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.160448 | nan |
| auc | 0.978757 | nan |
| f1 | 0.964758 | 0.523377 |
| accuracy | 0.965066 | 0.523377 |
| precision | 1 | 0.986192 |
| recall | 1 | 0.00049015 |
| mcc | 0.930273 | 0.523377 |
| score | threshold | |
|---|---|---|
| logloss | 0.160448 | nan |
| auc | 0.978757 | nan |
| f1 | 0.964758 | 0.523377 |
| accuracy | 0.965066 | 0.523377 |
| precision | 0.973333 | 0.523377 |
| recall | 0.956332 | 0.523377 |
| mcc | 0.930273 | 0.523377 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 223 | 6 |
| Labeled as 1 | 10 | 219 |
average_precision
34.8 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.277206 | nan |
| auc | 0.986366 | nan |
| f1 | 0.964758 | 0.466563 |
| accuracy | 0.965066 | 0.466563 |
| precision | 1 | 0.769136 |
| recall | 1 | 0.0228478 |
| mcc | 0.930273 | 0.466563 |
| score | threshold | |
|---|---|---|
| logloss | 0.277206 | nan |
| auc | 0.986366 | nan |
| f1 | 0.964758 | 0.466563 |
| accuracy | 0.965066 | 0.466563 |
| precision | 0.973333 | 0.466563 |
| recall | 0.956332 | 0.466563 |
| mcc | 0.930273 | 0.466563 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 223 | 6 |
| Labeled as 1 | 10 | 219 |
average_precision
38.6 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.152502 | nan |
| auc | 0.984783 | nan |
| f1 | 0.960699 | 0.339953 |
| accuracy | 0.960699 | 0.339953 |
| precision | 1 | 0.956087 |
| recall | 1 | 0.000692652 |
| mcc | 0.921538 | 0.386385 |
| score | threshold | |
|---|---|---|
| logloss | 0.152502 | nan |
| auc | 0.984783 | nan |
| f1 | 0.960699 | 0.339953 |
| accuracy | 0.960699 | 0.339953 |
| precision | 0.960699 | 0.339953 |
| recall | 0.960699 | 0.339953 |
| mcc | 0.921397 | 0.339953 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 220 | 9 |
| Labeled as 1 | 9 | 220 |
average_precision
35.4 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.259149 | nan |
| auc | 0.978185 | nan |
| f1 | 0.955947 | 0.453944 |
| accuracy | 0.956332 | 0.453944 |
| precision | 1 | 0.934871 |
| recall | 1 | 0.000595822 |
| mcc | 0.912803 | 0.453944 |
| score | threshold | |
|---|---|---|
| logloss | 0.259149 | nan |
| auc | 0.978185 | nan |
| f1 | 0.955947 | 0.453944 |
| accuracy | 0.956332 | 0.453944 |
| precision | 0.964444 | 0.453944 |
| recall | 0.947598 | 0.453944 |
| mcc | 0.912803 | 0.453944 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 221 | 8 |
| Labeled as 1 | 12 | 217 |
average_precision
35.6 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.270773 | nan |
| auc | 0.978719 | nan |
| f1 | 0.955947 | 0.465674 |
| accuracy | 0.956332 | 0.465674 |
| precision | 1 | 0.930674 |
| recall | 1 | 0.000994834 |
| mcc | 0.913919 | 0.497215 |
| score | threshold | |
|---|---|---|
| logloss | 0.270773 | nan |
| auc | 0.978719 | nan |
| f1 | 0.955947 | 0.465674 |
| accuracy | 0.956332 | 0.465674 |
| precision | 0.964444 | 0.465674 |
| recall | 0.947598 | 0.465674 |
| mcc | 0.912803 | 0.465674 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 221 | 8 |
| Labeled as 1 | 12 | 217 |
average_precision
35.7 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.209303 | nan |
| auc | 0.983896 | nan |
| f1 | 0.969432 | 0.388947 |
| accuracy | 0.969432 | 0.388947 |
| precision | 1 | 0.900033 |
| recall | 1 | 0.000418861 |
| mcc | 0.938865 | 0.388947 |
| score | threshold | |
|---|---|---|
| logloss | 0.209303 | nan |
| auc | 0.983896 | nan |
| f1 | 0.969432 | 0.388947 |
| accuracy | 0.969432 | 0.388947 |
| precision | 0.969432 | 0.388947 |
| recall | 0.969432 | 0.388947 |
| mcc | 0.938865 | 0.388947 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 222 | 7 |
| Labeled as 1 | 7 | 222 |
average_precision
37.5 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.206201 | nan |
| auc | 0.984726 | nan |
| f1 | 0.955947 | 0.522409 |
| accuracy | 0.956332 | 0.522409 |
| precision | 1 | 0.85675 |
| recall | 1 | 0.0194263 |
| mcc | 0.913221 | 0.56226 |
| score | threshold | |
|---|---|---|
| logloss | 0.206201 | nan |
| auc | 0.984726 | nan |
| f1 | 0.955947 | 0.522409 |
| accuracy | 0.956332 | 0.522409 |
| precision | 0.964444 | 0.522409 |
| recall | 0.947598 | 0.522409 |
| mcc | 0.912803 | 0.522409 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 221 | 8 |
| Labeled as 1 | 12 | 217 |
average_precision
39.4 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.217276 | nan |
| auc | 0.976726 | nan |
| f1 | 0.936937 | 0.62466 |
| accuracy | 0.938865 | 0.62466 |
| precision | 1 | 0.74639 |
| recall | 1 | 0.00407834 |
| mcc | 0.879374 | 0.62466 |
| score | threshold | |
|---|---|---|
| logloss | 0.217276 | nan |
| auc | 0.976726 | nan |
| f1 | 0.936937 | 0.62466 |
| accuracy | 0.938865 | 0.62466 |
| precision | 0.967442 | 0.62466 |
| recall | 0.908297 | 0.62466 |
| mcc | 0.879374 | 0.62466 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 222 | 7 |
| Labeled as 1 | 21 | 208 |
average_precision
36.4 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.192042 | nan |
| auc | 0.974028 | nan |
| f1 | 0.941176 | 0.538017 |
| accuracy | 0.943231 | 0.538017 |
| precision | 1 | 0.88594 |
| recall | 1 | 0.00697453 |
| mcc | 0.888635 | 0.538017 |
| score | threshold | |
|---|---|---|
| logloss | 0.192042 | nan |
| auc | 0.974028 | nan |
| f1 | 0.941176 | 0.538017 |
| accuracy | 0.943231 | 0.538017 |
| precision | 0.976526 | 0.538017 |
| recall | 0.908297 | 0.538017 |
| mcc | 0.888635 | 0.538017 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 224 | 5 |
| Labeled as 1 | 21 | 208 |
| feature | Learner_1 | Learner_2 | Learner_3 | Learner_4 | Learner_5 |
|---|---|---|---|---|---|
| PEER_PRESSURE | 2.09855 | 1.97751 | 2.10596 | 2.24214 | 2.11845 |
| ALLERGY | 1.71851 | 1.8115 | 1.80494 | 1.6434 | 1.99987 |
| CHRONIC DISEASE | 1.87657 | 1.63242 | 1.72145 | 1.71654 | 1.80335 |
| YELLOW_FINGERS | 1.60769 | 1.59401 | 1.57961 | 1.70178 | 1.69653 |
| SWALLOWING DIFFICULTY | 1.54115 | 1.39416 | 1.52935 | 1.57504 | 1.50732 |
| COUGHING | 1.6269 | 1.44695 | 1.61924 | 1.30983 | 1.45889 |
| WHEEZING | 1.39098 | 1.33944 | 1.35351 | 1.6218 | 1.23305 |
| ALCOHOL CONSUMING | 1.2172 | 1.51097 | 1.01974 | 1.43756 | 1.6208 |
| FATIGUE | 1.22949 | 1.23666 | 1.24562 | 1.05542 | 1.27239 |
| ANXIETY | 0.676465 | 1.11655 | 0.820949 | 1.03973 | 0.927658 |
| CHEST PAIN | 0.451082 | 0.609851 | 0.301484 | 0.389733 | 0.68452 |
| SMOKING | 0.404751 | 0.352542 | 0.398707 | 0.489795 | 0.317827 |
| SHORTNESS OF BREATH | 0.222579 | 0.360146 | 0.254631 | 0.399099 | 0.113896 |
| AGE | -0.0683001 | 0.0651653 | 0.0293103 | -0.0196802 | 0.14053 |
| GENDER | -0.0705105 | -0.180772 | -0.240995 | -0.128562 | 0.147742 |
| intercept | -4.88958 | -5.06286 | -4.78165 | -5.16035 | -5.28215 |
average_precision
36.5 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.239429 | nan |
| auc | 0.980273 | nan |
| f1 | 0.933628 | 0.568717 |
| accuracy | 0.934498 | 0.568717 |
| precision | 1 | 0.659086 |
| recall | 1 | 0 |
| mcc | 0.872329 | 0.610506 |
| score | threshold | |
|---|---|---|
| logloss | 0.239429 | nan |
| auc | 0.980273 | nan |
| f1 | 0.933628 | 0.568717 |
| accuracy | 0.934498 | 0.568717 |
| precision | 0.946188 | 0.568717 |
| recall | 0.921397 | 0.568717 |
| mcc | 0.869294 | 0.568717 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 217 | 12 |
| Labeled as 1 | 18 | 211 |
average_precision
38.8 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.287469 | nan |
| auc | 0.963864 | nan |
| f1 | 0.902386 | 0.594454 |
| accuracy | 0.901747 | 0.594454 |
| precision | 1 | 0.73422 |
| recall | 1 | 0.0325234 |
| mcc | 0.803562 | 0.594454 |
| score | threshold | |
|---|---|---|
| logloss | 0.287469 | nan |
| auc | 0.963864 | nan |
| f1 | 0.902386 | 0.594454 |
| accuracy | 0.901747 | 0.594454 |
| precision | 0.896552 | 0.594454 |
| recall | 0.908297 | 0.594454 |
| mcc | 0.803562 | 0.594454 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 205 | 24 |
| Labeled as 1 | 21 | 208 |
average_precision
37.4 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.292899 | nan |
| auc | 0.968851 | nan |
| f1 | 0.912134 | 0.579257 |
| accuracy | 0.908297 | 0.579257 |
| precision | 1 | 0.719996 |
| recall | 1 | 0 |
| mcc | 0.819726 | 0.579257 |
| score | threshold | |
|---|---|---|
| logloss | 0.292899 | nan |
| auc | 0.968851 | nan |
| f1 | 0.912134 | 0.579257 |
| accuracy | 0.908297 | 0.579257 |
| precision | 0.875502 | 0.579257 |
| recall | 0.951965 | 0.579257 |
| mcc | 0.819726 | 0.579257 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 198 | 31 |
| Labeled as 1 | 11 | 218 |
average_precision
32.1 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.232964 | nan |
| auc | 0.976917 | nan |
| f1 | 0.944321 | 0.492837 |
| accuracy | 0.945415 | 0.492837 |
| precision | 1 | 0.99338 |
| recall | 1 | 6.41845e-12 |
| mcc | 0.891518 | 0.492837 |
| score | threshold | |
|---|---|---|
| logloss | 0.232964 | nan |
| auc | 0.976917 | nan |
| f1 | 0.944321 | 0.492837 |
| accuracy | 0.945415 | 0.492837 |
| precision | 0.963636 | 0.492837 |
| recall | 0.925764 | 0.492837 |
| mcc | 0.891518 | 0.492837 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 221 | 8 |
| Labeled as 1 | 17 | 212 |
average_precision
34.1 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.192402 | nan |
| auc | 0.974066 | nan |
| f1 | 0.944321 | 0.509772 |
| accuracy | 0.945415 | 0.509772 |
| precision | 1 | 0.999026 |
| recall | 1 | 0.000268946 |
| mcc | 0.891518 | 0.509772 |
| score | threshold | |
|---|---|---|
| logloss | 0.192402 | nan |
| auc | 0.974066 | nan |
| f1 | 0.944321 | 0.509772 |
| accuracy | 0.945415 | 0.509772 |
| precision | 0.963636 | 0.509772 |
| recall | 0.925764 | 0.509772 |
| mcc | 0.891518 | 0.509772 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 221 | 8 |
| Labeled as 1 | 17 | 212 |
average_precision
34.0 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.244839 | nan |
| auc | 0.966877 | nan |
| f1 | 0.938865 | 0.505872 |
| accuracy | 0.938865 | 0.505872 |
| precision | 1 | 0.991168 |
| recall | 1 | 4.76261e-06 |
| mcc | 0.877863 | 0.551479 |
| score | threshold | |
|---|---|---|
| logloss | 0.244839 | nan |
| auc | 0.966877 | nan |
| f1 | 0.938865 | 0.505872 |
| accuracy | 0.938865 | 0.505872 |
| precision | 0.938865 | 0.505872 |
| recall | 0.938865 | 0.505872 |
| mcc | 0.877729 | 0.505872 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 215 | 14 |
| Labeled as 1 | 14 | 215 |
average_precision
33.4 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.190663 | nan |
| auc | 0.979119 | nan |
| f1 | 0.947598 | 0.46477 |
| accuracy | 0.947598 | 0.46477 |
| precision | 1 | 0.999892 |
| recall | 1 | 4.76882e-06 |
| mcc | 0.895197 | 0.46477 |
| score | threshold | |
|---|---|---|
| logloss | 0.190663 | nan |
| auc | 0.979119 | nan |
| f1 | 0.947598 | 0.46477 |
| accuracy | 0.947598 | 0.46477 |
| precision | 0.947598 | 0.46477 |
| recall | 0.947598 | 0.46477 |
| mcc | 0.895197 | 0.46477 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 217 | 12 |
| Labeled as 1 | 12 | 217 |
average_precision
36.2 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.133128 | nan |
| auc | 0.987186 | nan |
| f1 | 0.962801 | 0.40466 |
| accuracy | 0.962882 | 0.40466 |
| precision | 1 | 0.91199 |
| recall | 1 | 0.00263693 |
| mcc | 0.925773 | 0.40466 |
| score | threshold | |
|---|---|---|
| logloss | 0.133128 | nan |
| auc | 0.987186 | nan |
| f1 | 0.962801 | 0.40466 |
| accuracy | 0.962882 | 0.40466 |
| precision | 0.964912 | 0.40466 |
| recall | 0.960699 | 0.40466 |
| mcc | 0.925773 | 0.40466 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 221 | 8 |
| Labeled as 1 | 9 | 220 |
average_precision
36.7 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.304858 | nan |
| auc | 0.979196 | nan |
| f1 | 0.95671 | 0.456 |
| accuracy | 0.956332 | 0.456 |
| precision | 1 | 0.85841 |
| recall | 1 | 0.0111083 |
| mcc | 0.913221 | 0.505393 |
| score | threshold | |
|---|---|---|
| logloss | 0.304858 | nan |
| auc | 0.979196 | nan |
| f1 | 0.95671 | 0.456 |
| accuracy | 0.956332 | 0.456 |
| precision | 0.948498 | 0.456 |
| recall | 0.965066 | 0.456 |
| mcc | 0.912803 | 0.456 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 217 | 12 |
| Labeled as 1 | 8 | 221 |
average_precision
37.4 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.407641 | nan |
| auc | 0.987939 | nan |
| f1 | 0.969298 | 0.478908 |
| accuracy | 0.969432 | 0.478908 |
| precision | 1 | 0.601983 |
| recall | 1 | 0.100235 |
| mcc | 0.939008 | 0.487179 |
| score | threshold | |
|---|---|---|
| logloss | 0.407641 | nan |
| auc | 0.987939 | nan |
| f1 | 0.969298 | 0.478908 |
| accuracy | 0.969432 | 0.478908 |
| precision | 0.973568 | 0.478908 |
| recall | 0.965066 | 0.478908 |
| mcc | 0.9389 | 0.478908 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 223 | 6 |
| Labeled as 1 | 8 | 221 |
average_precision
33.1 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.200297 | nan |
| auc | 0.980283 | nan |
| f1 | 0.955947 | 0.487291 |
| accuracy | 0.956332 | 0.487291 |
| precision | 1 | 0.921339 |
| recall | 1 | 0.000282286 |
| mcc | 0.912803 | 0.487291 |
| score | threshold | |
|---|---|---|
| logloss | 0.200297 | nan |
| auc | 0.980283 | nan |
| f1 | 0.955947 | 0.487291 |
| accuracy | 0.956332 | 0.487291 |
| precision | 0.964444 | 0.487291 |
| recall | 0.947598 | 0.487291 |
| mcc | 0.912803 | 0.487291 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 221 | 8 |
| Labeled as 1 | 12 | 217 |
average_precision
39.4 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.193748 | nan |
| auc | 0.983343 | nan |
| f1 | 0.951965 | 0.480871 |
| accuracy | 0.951965 | 0.480871 |
| precision | 1 | 0.897608 |
| recall | 1 | 0.0198381 |
| mcc | 0.90393 | 0.480871 |
| score | threshold | |
|---|---|---|
| logloss | 0.193748 | nan |
| auc | 0.983343 | nan |
| f1 | 0.951965 | 0.480871 |
| accuracy | 0.951965 | 0.480871 |
| precision | 0.951965 | 0.480871 |
| recall | 0.951965 | 0.480871 |
| mcc | 0.90393 | 0.480871 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 218 | 11 |
| Labeled as 1 | 11 | 218 |
average_precision
39.6 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.240876 | nan |
| auc | 0.982037 | nan |
| f1 | 0.946188 | 0.586479 |
| accuracy | 0.947598 | 0.586479 |
| precision | 1 | 0.783775 |
| recall | 1 | 0.0184963 |
| mcc | 0.89739 | 0.605179 |
| score | threshold | |
|---|---|---|
| logloss | 0.240876 | nan |
| auc | 0.982037 | nan |
| f1 | 0.946188 | 0.586479 |
| accuracy | 0.947598 | 0.586479 |
| precision | 0.97235 | 0.586479 |
| recall | 0.921397 | 0.586479 |
| mcc | 0.896428 | 0.586479 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 223 | 6 |
| Labeled as 1 | 18 | 211 |
average_precision
36.9 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.218303 | nan |
| auc | 0.982485 | nan |
| f1 | 0.95671 | 0.479353 |
| accuracy | 0.956332 | 0.479353 |
| precision | 1 | 0.88041 |
| recall | 1 | 0.000316717 |
| mcc | 0.913221 | 0.528092 |
| score | threshold | |
|---|---|---|
| logloss | 0.218303 | nan |
| auc | 0.982485 | nan |
| f1 | 0.95671 | 0.479353 |
| accuracy | 0.956332 | 0.479353 |
| precision | 0.948498 | 0.479353 |
| recall | 0.965066 | 0.479353 |
| mcc | 0.912803 | 0.479353 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 217 | 12 |
| Labeled as 1 | 8 | 221 |
average_precision
37.1 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.200515 | nan |
| auc | 0.982628 | nan |
| f1 | 0.960699 | 0.469438 |
| accuracy | 0.960699 | 0.469438 |
| precision | 1 | 0.925408 |
| recall | 1 | 0.000141272 |
| mcc | 0.921397 | 0.469438 |
| score | threshold | |
|---|---|---|
| logloss | 0.200515 | nan |
| auc | 0.982628 | nan |
| f1 | 0.960699 | 0.469438 |
| accuracy | 0.960699 | 0.469438 |
| precision | 0.960699 | 0.469438 |
| recall | 0.960699 | 0.469438 |
| mcc | 0.921397 | 0.469438 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 220 | 9 |
| Labeled as 1 | 9 | 220 |
average_precision
36.3 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.183978 | nan |
| auc | 0.982323 | nan |
| f1 | 0.952381 | 0.417404 |
| accuracy | 0.951965 | 0.417404 |
| precision | 1 | 0.91976 |
| recall | 1 | 0.00294066 |
| mcc | 0.904482 | 0.537173 |
| score | threshold | |
|---|---|---|
| logloss | 0.183978 | nan |
| auc | 0.982323 | nan |
| f1 | 0.952381 | 0.417404 |
| accuracy | 0.951965 | 0.417404 |
| precision | 0.944206 | 0.417404 |
| recall | 0.960699 | 0.417404 |
| mcc | 0.904068 | 0.417404 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 216 | 13 |
| Labeled as 1 | 9 | 220 |
average_precision
37.5 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.136098 | nan |
| auc | 0.985183 | nan |
| f1 | 0.965066 | 0.414042 |
| accuracy | 0.965066 | 0.414042 |
| precision | 1 | 0.953703 |
| recall | 1 | 0.000352897 |
| mcc | 0.930131 | 0.414042 |
| score | threshold | |
|---|---|---|
| logloss | 0.136098 | nan |
| auc | 0.985183 | nan |
| f1 | 0.965066 | 0.414042 |
| accuracy | 0.965066 | 0.414042 |
| precision | 0.965066 | 0.414042 |
| recall | 0.965066 | 0.414042 |
| mcc | 0.930131 | 0.414042 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 221 | 8 |
| Labeled as 1 | 8 | 221 |
average_precision
38.1 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.142383 | nan |
| auc | 0.983982 | nan |
| f1 | 0.960699 | 0.351742 |
| accuracy | 0.960699 | 0.351742 |
| precision | 1 | 0.961723 |
| recall | 1 | 0.000341111 |
| mcc | 0.921397 | 0.351742 |
| score | threshold | |
|---|---|---|
| logloss | 0.142383 | nan |
| auc | 0.983982 | nan |
| f1 | 0.960699 | 0.351742 |
| accuracy | 0.960699 | 0.351742 |
| precision | 0.960699 | 0.351742 |
| recall | 0.960699 | 0.351742 |
| mcc | 0.921397 | 0.351742 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 220 | 9 |
| Labeled as 1 | 9 | 220 |
average_precision
37.5 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.230157 | nan |
| auc | 0.981751 | nan |
| f1 | 0.960699 | 0.430041 |
| accuracy | 0.960699 | 0.430041 |
| precision | 1 | 0.816499 |
| recall | 1 | 0.000807625 |
| mcc | 0.921538 | 0.518465 |
| score | threshold | |
|---|---|---|
| logloss | 0.230157 | nan |
| auc | 0.981751 | nan |
| f1 | 0.960699 | 0.430041 |
| accuracy | 0.960699 | 0.430041 |
| precision | 0.960699 | 0.430041 |
| recall | 0.960699 | 0.430041 |
| mcc | 0.921397 | 0.430041 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 220 | 9 |
| Labeled as 1 | 9 | 220 |
average_precision
38.3 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.343602 | nan |
| auc | 0.97992 | nan |
| f1 | 0.964758 | 0.495033 |
| accuracy | 0.965066 | 0.495033 |
| precision | 1 | 0.745898 |
| recall | 1 | 0.00942796 |
| mcc | 0.930273 | 0.495033 |
| score | threshold | |
|---|---|---|
| logloss | 0.343602 | nan |
| auc | 0.97992 | nan |
| f1 | 0.964758 | 0.495033 |
| accuracy | 0.965066 | 0.495033 |
| precision | 0.973333 | 0.495033 |
| recall | 0.956332 | 0.495033 |
| mcc | 0.930273 | 0.495033 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 223 | 6 |
| Labeled as 1 | 10 | 219 |
average_precision
32.6 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.229284 | nan |
| auc | 0.973904 | nan |
| f1 | 0.95614 | 0.371413 |
| accuracy | 0.956332 | 0.371413 |
| precision | 1 | 0.909043 |
| recall | 1 | 0.000912171 |
| mcc | 0.913221 | 0.49942 |
| score | threshold | |
|---|---|---|
| logloss | 0.229284 | nan |
| auc | 0.973904 | nan |
| f1 | 0.95614 | 0.371413 |
| accuracy | 0.956332 | 0.371413 |
| precision | 0.960352 | 0.371413 |
| recall | 0.951965 | 0.371413 |
| mcc | 0.912699 | 0.371413 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 220 | 9 |
| Labeled as 1 | 11 | 218 |
average_precision
33.3 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.15605 | nan |
| auc | 0.986175 | nan |
| f1 | 0.960699 | 0.318487 |
| accuracy | 0.960699 | 0.318487 |
| precision | 1 | 0.930107 |
| recall | 1 | 0.00245639 |
| mcc | 0.921397 | 0.318487 |
| score | threshold | |
|---|---|---|
| logloss | 0.15605 | nan |
| auc | 0.986175 | nan |
| f1 | 0.960699 | 0.318487 |
| accuracy | 0.960699 | 0.318487 |
| precision | 0.960699 | 0.318487 |
| recall | 0.960699 | 0.318487 |
| mcc | 0.921397 | 0.318487 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 220 | 9 |
| Labeled as 1 | 9 | 220 |
average_precision
36.9 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.136959 | nan |
| auc | 0.986251 | nan |
| f1 | 0.961039 | 0.328352 |
| accuracy | 0.960699 | 0.328352 |
| precision | 1 | 0.95644 |
| recall | 1 | 0.00051573 |
| mcc | 0.921538 | 0.328352 |
| score | threshold | |
|---|---|---|
| logloss | 0.136959 | nan |
| auc | 0.986251 | nan |
| f1 | 0.961039 | 0.328352 |
| accuracy | 0.960699 | 0.328352 |
| precision | 0.95279 | 0.328352 |
| recall | 0.969432 | 0.328352 |
| mcc | 0.921538 | 0.328352 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 218 | 11 |
| Labeled as 1 | 7 | 222 |
average_precision
31.5 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.261498 | nan |
| auc | 0.969814 | nan |
| f1 | 0.942731 | 0.422963 |
| accuracy | 0.943231 | 0.422963 |
| precision | 1 | 0.999584 |
| recall | 1 | 2.82294e-13 |
| mcc | 0.886598 | 0.422963 |
| score | threshold | |
|---|---|---|
| logloss | 0.261498 | nan |
| auc | 0.969814 | nan |
| f1 | 0.942731 | 0.422963 |
| accuracy | 0.943231 | 0.422963 |
| precision | 0.951111 | 0.422963 |
| recall | 0.934498 | 0.422963 |
| mcc | 0.886598 | 0.422963 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 218 | 11 |
| Labeled as 1 | 15 | 214 |
average_precision
35.0 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.244857 | nan |
| auc | 0.973008 | nan |
| f1 | 0.929204 | 0.543938 |
| accuracy | 0.930131 | 0.543938 |
| precision | 1 | 0.809828 |
| recall | 1 | 0.00924381 |
| mcc | 0.860557 | 0.543938 |
| score | threshold | |
|---|---|---|
| logloss | 0.244857 | nan |
| auc | 0.973008 | nan |
| f1 | 0.929204 | 0.543938 |
| accuracy | 0.930131 | 0.543938 |
| precision | 0.941704 | 0.543938 |
| recall | 0.917031 | 0.543938 |
| mcc | 0.860557 | 0.543938 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 216 | 13 |
| Labeled as 1 | 19 | 210 |
average_precision
34.4 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.213265 | nan |
| auc | 0.978061 | nan |
| f1 | 0.948052 | 0.454949 |
| accuracy | 0.947598 | 0.454949 |
| precision | 1 | 0.914193 |
| recall | 1 | 0.00285144 |
| mcc | 0.895333 | 0.454949 |
| score | threshold | |
|---|---|---|
| logloss | 0.213265 | nan |
| auc | 0.978061 | nan |
| f1 | 0.948052 | 0.454949 |
| accuracy | 0.947598 | 0.454949 |
| precision | 0.939914 | 0.454949 |
| recall | 0.956332 | 0.454949 |
| mcc | 0.895333 | 0.454949 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 215 | 14 |
| Labeled as 1 | 10 | 219 |
average_precision
32.8 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.224115 | nan |
| auc | 0.973828 | nan |
| f1 | 0.955947 | 0.513647 |
| accuracy | 0.956332 | 0.513647 |
| precision | 1 | 0.893619 |
| recall | 1 | 0.000621553 |
| mcc | 0.913221 | 0.560704 |
| score | threshold | |
|---|---|---|
| logloss | 0.224115 | nan |
| auc | 0.973828 | nan |
| f1 | 0.955947 | 0.513647 |
| accuracy | 0.956332 | 0.513647 |
| precision | 0.964444 | 0.513647 |
| recall | 0.947598 | 0.513647 |
| mcc | 0.912803 | 0.513647 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 221 | 8 |
| Labeled as 1 | 12 | 217 |
average_precision
34.1 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.389888 | nan |
| auc | 0.923438 | nan |
| f1 | 0.874459 | 0.496016 |
| accuracy | 0.873362 | 0.496016 |
| precision | 0.933333 | 0.678531 |
| recall | 1 | 0.0807524 |
| mcc | 0.748554 | 0.555026 |
| score | threshold | |
|---|---|---|
| logloss | 0.389888 | nan |
| auc | 0.923438 | nan |
| f1 | 0.874459 | 0.496016 |
| accuracy | 0.873362 | 0.496016 |
| precision | 0.866953 | 0.496016 |
| recall | 0.882096 | 0.496016 |
| mcc | 0.746839 | 0.496016 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 198 | 31 |
| Labeled as 1 | 27 | 202 |
| Model | Weight |
|---|---|
| 10_Xgboost | 19 |
| 27_CatBoost_GoldenFeatures | 1 |
| 29_CatBoost | 4 |
| 36_CatBoost_GoldenFeatures | 3 |
| 4_Default_CatBoost_GoldenFeatures | 2 |
| 5_Default_NeuralNetwork | 1 |
| score | threshold | |
|---|---|---|
| logloss | 0.481864 | nan |
| auc | 0.990752 | nan |
| f1 | 0.961039 | 0.433141 |
| accuracy | 0.960699 | 0.433141 |
| precision | 1 | 0.592046 |
| recall | 1 | 0.303875 |
| mcc | 0.921538 | 0.433141 |
| score | threshold | |
|---|---|---|
| logloss | 0.481864 | nan |
| auc | 0.990752 | nan |
| f1 | 0.961039 | 0.433141 |
| accuracy | 0.960699 | 0.433141 |
| precision | 0.95279 | 0.433141 |
| recall | 0.969432 | 0.433141 |
| mcc | 0.921538 | 0.433141 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 218 | 11 |
| Labeled as 1 | 7 | 222 |